This course provides a comprehensive introduction to machine learning, covering essential algorithms, models, and methods. Students will explore supervised and unsupervised learning, data preprocessing, model evaluation, and various applications of machine learning in real-world scenarios. The course balances theory with practical, hands-on projects to reinforce concepts and techniques.
By the end of the course, students will be able to:
Sateesh A, bringing extensive expertise in AI-driven healthcare solutions. With a background in Engineering (B.E., M.Tech., and Ph.D. in AI for Healthcare), Sateesh has over two decades of experience in technology innovation, spanning roles in top organizations like Samsung, Intel, and Sandisk.
His work focuses on developing advanced AI models for healthcare, including federated learning frameworks, synthetic data generation, and explainable AI models for predictive healthcare applications.
Sateesh has led multiple groundbreaking research projects, authored numerous publications, and presented at international conferences, advancing the field of adaptive, teacher-less education platforms. His vision is to make high-quality education accessible to remote regions through AI, helping learners achieve employability and lifelong learning.
Sateesh’s achievements include recognition as a top tech innovator, participation in elite accelerator programs, and collaboration with esteemed institutions like Stanford, IIIT-B, and IIM-A.
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